There are various applications where it is desirable to monitor traffic flow along one or more roads. For instance there may be a desire to determine the amount of traffic on a given part of a road network and/or the flow of the traffic on that part of the network. Such information may be required for implementing adaptive traffic management techniques. For instance variable speed limits may be set according to the volume and flow of traffic on a given stretch of road. The operation of traffic lights or other signal controls to control access to a given section of road may be controlled based on knowledge of the traffic flow at various parts of the network. Contraflow systems or other lane controls may be activated or controlled based on such information.
Additionally or alternatively information about the volume and flow of traffic on various parts of the road network will be of use to traffic managers even if the network or parts thereof do not have active traffic management systems to provide data to allow modelling of any improvements to the general traffic management, such as permanent alterations in speed limits or changes to road markings or signage for example.
Collection of data about traffic flow before and after any changes will also be useful to determine how any changes have impacted traffic flow. Data on traffic flow will also be useful to planners for planning any upgrades or additions to the road network and may also be useful for incident management, for example in terms of opening and/or closing various diversion routes based on traffic patterns.
Also data on the volume of traffic travelling on sections of the road network may be of interest for those responsible for maintaining the network to allow decisions about regular maintenance based on likely wear.
Various types of road traffic monitoring systems exist.
Pressure or strain based sensors, for instance based on piezoelectric sensors or pneumatic hoses, may be laid, or embedded, across a carriageway and monitored to detect the weight of a vehicle crossing over the sensor. Such sensors will effectively act as axle counters and can be arranged to monitor volume of traffic and flow rate at a given point and also estimate generally the type of vehicle. Such sensors are useful and relatively simple but each lane of a multi-lane highway will require its own sensor and multiple sensors will be required at different points along a traffic network in order to be able to monitor traffic along the network. Sensor strips or hoses laid across the surface of a road will also be subject to relatively severe wear and tear requiring robust sensors and/or regular maintenance. Sensors embedded within a highway will be less exposed but will typically require more work to be installed and are much harder to access for repair or maintenance.
Inductive sensors can be used based on induction loops embedded within the carriageway. Passage of a vehicle produces eddy currents which can be detected. Induction loop traffic sensors are widely used in a range of applications and can provide information about traffic volume and flow and an estimate of vehicle type. Again however a separate induction loop must be provided for each lane of a multi-lane highway and multiple sensors along the road must be used to provide information about general traffic flow along the network, limiting overall resolution. The sensors are embedded within the carriageway with the associated costs and inconvenience of installation and difficulty of maintenance. Magnetic sensors using embedded magnetic detectors have also been proposed but have similar issues to inductive sensors.
Radar based sensors, for instance microwave radars, have also been used. The radar system may be mounted on an overhead gantry or bridge to transmit pulses of radiation along a lane of a carriageway. Returns from vehicles can be detected and the speed of the vehicle detected—either from a Doppler shift or by tracking the movement along the lane. Lidar based systems, e.g., IR based lidar, may use a similar approach or may simply scan for vehicles crossing under a scanned area. Such sensors may be relatively expensive however and need to be mounted with a good view of the road to be monitored which, as mentioned may require the presence of overhead structures—which may be not be available in various parts of the network.
Increasingly video processing is being used for traffic monitoring. Video images of the road network may be observed by control personnel to get a feel for the current traffic conditions to allow control decisions to be made but automatic image processing may also allow automatic detection of volume and flow of traffic. Image processing techniques such as pattern recognition and edge detection may be used to identify and track vehicles and potentially categorise the type of vehicle. In addition automatic number plate recognition may be applied to identify the number plate/licence plate of the vehicle. This can allow more sophisticated tracking of individual vehicles around the traffic network and, with access to a database of vehicle registrations, the type of vehicle can be identified from identifying the number plate. However again this requires multiple relatively high quality cameras positioned with good views of the roads to be monitored.
GPS based traffic monitoring has also been proposed, the idea being that at least some vehicles are equipped with a GPS tracker and a transmitter so as to transmit information about their location and speed to a central server. In theory the GPS equipment could be a requirement for every vehicle but in practice the system may possibly make use of any GPS device that the driver may possess, such as a navigational aid or smartphone, or provide dedicated GPS equipment to just a proportion of the vehicles that regularly travel on the road network of interest. With enough vehicles transmitting data it will be possible to monitor general flow rates of traffic on various parts of the network. However such methods are likely to be of limited use in low traffic volumes, may not provide enough accuracy to determine lane usage of a multi-lane road and may struggle in tunnels or mountainous regions where the GPS signals may be lost. This approach may also require vehicle owners to consent to being tracked and the data may be collected by a different entity to the one managing the road network.